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In general, we have found the JSLDS loss function strengths to be relatively easy to select (see example settings in the specific experiment sections below). RNN's fixed points or slow points would defeat the primary purpose of the method. However, other variations are possible. We set the number of timesteps T = 25. We trained both methods with the Adam optimizer with default settings.

In "Stein Variational Gradient Descent as Moment Matching," the authors first introduce the algorithm known as Stein Variational Gradient Descent (SVGD). While some work has been done trying to provide a theoretical analysis of this method, the consistency of SVGD is largely still open for finite sizes of n. By studying the fixed point solution to SVGD, they show there are a set of functions for which the the fixed point solution perfectly estimates their mean under the target distribution (they call this the Stein set of functions). They argue that using a polynomial kernel when the target is a Gaussian will force any fixed point solution of SVGD to exactly estimate the mean and covariance of the target distribution, assuming the SVGD solution points are full rank. The major contribution of this paper is that by studying the properties of finite dimensional kernels, they are able to employ random Fourier features to provide a theoretical analysis of the fixed points for these "randomized" kernels.

Welcome to AI book reviews, a series of posts that explore the latest literature on artificial intelligence. Despite its promising advances, artificial intelligence has yet to cause a transformational change in many industries. And in many cases, the problem is not necessarily with the technology but with the way we perceive it. Power and Prediction, a new book by Ajay Agrawal, Joshua Gans, and Avi Goldfarb, explores the fundamental challenges standing in the way of AI adoption in different industries. A sequel to their acclaimed Prediction Machines, the new book discusses what needs to change before organizations can benefit from the full potential of advances in artificial intelligence.

Join us on November 9 to learn how to successfully innovate and achieve efficiency by upskilling and scaling citizen developers at the Low-Code/No-Code Summit. Many organizations are challenged with finding strategies to deal with rising customer volume and changes in expectations, while facing an uncertain business market, according to Genesys, a provider of contact center services. While they are pressured to deliver better experiences with less, many organizations are hamstrung by legacy business processes, siloed point solutions and insufficient technical resources. This is where artificial intelligence (AI) technologies have the potential to help, since most lack the data scientists and resources to implement and deploy technologies orientated around their customers and employees while still supporting business objectives, Genesys said. In a move to help organizations optimize customer journeys with new experience orchestration capabilities, Genesys last week unveiled Cloud AI Experience.

At Microsoft, we believe that energized, empowered employees are the key to a durable, competitive advantage for every organization. The Microsoft Work Trend Index shows that leaders today need to end productivity paranoia, embrace the fact that people come into the office for each other, and re-recruit everyone.1 Empowering today's digitally connected, distributed workforce requires the right culture and the right technology. At Microsoft Ignite, we're sharing new innovations across Microsoft 365, Microsoft Teams, and Microsoft Viva to help everyone thrive. Global experiences, localized content, in-person opportunities, and more--let's get ready for a new kind of Microsoft Ignite. Microsoft 365 is the cloud-first platform for all the ways that people work today--wherever, whenever, however.

Genesys, a global cloud leader in experience orchestration, today introduced Genesys Cloud AI Experience, a new solution designed to help organisations optimise customer journeys through accelerated experience innovation powered by smarter personalisation, automation and prediction. With the new solution, Genesys has expanded its experience orchestration capabilities, enabling organisations to listen and understand customers and employees through seamless coordination of technology, interactions and touchpoints. Now with greater ability to predict actions, automate journeys in real time and drive toward outcomes, Genesys Cloud AI Experience makes it possible for any organisation to orchestrate people-centric experiences at scale, fostering long-lasting relationships. Many organisations are challenged to find strategies for dealing with both rising customer volume and changes in expectations while facing an uncertain business market. With pressure to deliver better experiences with less, artificial intelligence (AI) technologies have the potential to help; yet many organisations are hamstrung by legacy business processes, siloed point solutions and insufficient technical resources.

AI takes on predictive power; humans retain judgement. There has been no shortage of attention given to the potential of artificial intelligence, along with related concerns about bias, data viability, costs, and employee resistance. But we may be missing the most important point when it comes to AI's ultimate impact, a leading AI proponent argues. That is, we're starting to outsource a large share of human decision-making to machines, which may have unforeseen implications -- beyond simply making cheaper predictions. It's time to start looking at AI not from a technologist's perspective, but from an economist's perspective, states Ajay Agrawal, professor at the University of Toronto, and co-author of Power and Prediction: The Disruptive Economics of Artificial Intelligence.

The pandemic has accelerated the onset of new technologies across industries. With artificial intelligence (AI) expected to grow by 21%, reaching $62 billion in 2022, it's no wonder nearly half of CIOs said they've either already deployed AI or plan to add it to their tech stacks in the next year. And with record-high numbers of Americans leaving their jobs, AI has moved from a "nice-to-have" technology to an essential way to optimize your teams' work and keep everyone feeling productive. The question for most businesses is no longer whether to adopt AI -- it's how to best integrate it into processes that scale with the company. Even though companies have spent the last two years implementing new technologies, often under tight deadlines and without a clear plan of what will come next, the process can still feel intimidating.

What is sales enablement, exactly? To most companies, it's providing sales organizations with the content, tools, and information they need to sell more effectively. Sales enablement is a broad-based goal, but one that can reap substantial benefits. According to Regalix -- which, it must be noted, has a vested interest in painting sales enablement solutions in a desirable light, given that it itself provides them -- 76% of organizations with a sales enablement function register an increase of sales between 6% to 20%. Investors see the value, or at least the revenue potential, in sales enablement technologies.